Accurate RNA splicing is essential for gene expression and human health, yet predicting how DNA sequence variations affect ...

Deep neural network models of sensory systems are often proposed to learn representational transformations with invariances like those in the brain. To reveal these invariances we generated "model ...

This demo shows how to use transformer networks to model the daily prices of stocks in MATLAB®. We will predict the price trends of three individual stocks and use the predicted time series values to ...

System identification learns models of dynamical systems from input–output measurements. Estimated models should generalize by predicting system’s output responses to new, previously unseen inputs.

In recent years, multivariate pattern analysis (MVPA) has been hugely beneficial for cognitive neuroscience by making new experiment designs possible and by increasing the inferential power of ...

Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of ...